In the computer vision context, many algorithms rely on the presence of visible texture to operate reliably. For example, algorithms involving stereoscopy may rely on texture for stereoscopic matching and/or for disparity computation. Algorithms using visual tracking or local “keypoints” may also rely on texture. However, many features of the real world, such as various man-made portions of the real world, may lack the necessary visual texture for the operation of such algorithms.
In some computer vision applications, texture projection, also referred to as structured light projection, may be used to provide visual texture for computer vision systems. For example, “RGB-D” cameras, which measure depth in addition to light intensity, may image the world based on structured light projection. Typically, structured light projection subsystems may be integrated with imaging subsystems, especially in systems requiring detailed calibration of the geometrical relationship between the projection and imaging subsystems. Systems and methods disclosed herein address various challenges related to structured light projection.